{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:13:47Z","timestamp":1760242427935,"version":"build-2065373602"},"reference-count":31,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2017,7,21]],"date-time":"2017-07-21T00:00:00Z","timestamp":1500595200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004663","name":"Ministry of Science and Technology, Taiwan","doi-asserted-by":"publisher","award":["MOST105-2410-H-194-059-MY3"],"award-info":[{"award-number":["MOST105-2410-H-194-059-MY3"]}],"id":[{"id":"10.13039\/501100004663","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Population ageing is an important global issue. The Taiwanese government has used various Internet of Things (IoT) applications in the \u201c10-year long-term care program 2.0\u201d. It is expected that the efficiency and effectiveness of long-term care services will be improved through IoT support. Home-delivered meal services for the elderly are important for home-based long-term care services. To ensure that the right meals are delivered to the right recipient at the right time, the runners need to take a picture of the meal recipient when the meal is delivered. This study uses the IoT-based image recognition system to design an integrated service to improve the management of image recognition. The core technology of this IoT-based image recognition system is statistical histogram-based k-means clustering for image segmentation. However, this method is time-consuming. Therefore, we proposed using the statistical histogram to obtain a probability density function of pixels of a figure and segmenting these with weighting for the same intensity. This aims to increase the computational performance and achieve the same results as k-means clustering. We combined histogram and k-means clustering in order to overcome the high computational cost for k-means clustering. The results indicate that the proposed method is significantly faster than k-means clustering by more than 10 times.<\/jats:p>","DOI":"10.3390\/sym9070125","type":"journal-article","created":{"date-parts":[[2017,7,21]],"date-time":"2017-07-21T10:45:48Z","timestamp":1500633948000},"page":"125","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["IoT-Based Image Recognition System for Smart Home-Delivered Meal Services"],"prefix":"10.3390","volume":"9","author":[{"given":"Hsiao-Ting","family":"Tseng","sequence":"first","affiliation":[{"name":"Institute of Information Management, National Chiao Tung University, Hsinchu 300, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hsin-Ginn","family":"Hwang","sequence":"additional","affiliation":[{"name":"Institute of Information Management, National Chiao Tung University, Hsinchu 300, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei-Yen","family":"Hsu","sequence":"additional","affiliation":[{"name":"Institute of Information Management, National Chung Cheng University, Chiayi 621, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pei-Chin","family":"Chou","sequence":"additional","affiliation":[{"name":"Institute of Information Management, National Chung Cheng University, Chiayi 621, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"I-Chiu","family":"Chang","sequence":"additional","affiliation":[{"name":"Institute of Information Management, National Chung Cheng University, Chiayi 621, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2017,7,21]]},"reference":[{"unstructured":"World Health Organization (2015). 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